Local Glioma Cells Are Associated with Vascular Dysregulation

Benign Glioma

Benign glioma broadly refers to a heterogeneous group of slow-growing glial tumors with low proliferative rates and a more indolent clinical course. These tumors may also be described as "low-grade" glioma (LGG) and are classified as WHO grade I or II lesions according to the Classification of Tumors of the Central Nervous System (CNS) (Louis et al. in Acta Neuropathol 114:97-109, 2007). Advances in molecular genetics have improved understanding of glioma tumorigenesis, leading to the identification of common mutation profiles with significant treatment and prognostic implications. The most recent WHO 2016 classification system has introduced several notable changes in the way that gliomas are diagnosed, with a new emphasis on molecular features as key factors in differentiation (Wesseling and Capper in Neuropathol Appl Neurobiol 44:139-150, 2018). Benign gliomas have a predilection for younger patients and are among the most frequently diagnosed tumors in children and young adults (Ostrom et al. in Neuro Oncol 22:iv1-iv96, 2020). These tumors can be separated into two clinically distinct subgroups. The first group is of focal, well-circumscribed lesions that notably are not associated with an increased risk of malignant transformation. Primarily diagnosed in pediatric patients, these WHO grade I tumors may be cured with surgical resection alone (Sturm et al. in J Clin Oncol 35:2370-2377, 2017). Recurrence rates are low, and the prognosis for these patients is excellent (Ostrom et al. in Neuro Oncol 22:iv1-iv96, 2020). Diffuse gliomas are WHO grade II lesions with a more infiltrative pattern of growth and high propensity for recurrence. These tumors are primarily diagnosed in young adult patients, and classically present with seizures (Pallud et al. Brain 137:449-462, 2014). The term "benign" is a misnomer in many cases, as the natural history of these tumors is with malignant transformation and recurrence as grade III or grade IV tumors (Jooma et al. in J Neurosurg 14:356-363, 2019). For all LGG, surgery with maximal safe resection is the treatment of choice for both primary and recurrent tumors. The goal of surgery should be for gross total resection (GTR), as complete tumor removal is associated with higher rates of tumor control and seizure freedom. Chemotherapy and radiation therapy (RT), while not typically a component of first-line treatment in most cases, may be employed as adjunctive therapy in high-risk or recurrent tumors and in some select cases. The prognosis of benign gliomas varies widely; non-infiltrative tumor subtypes generally have an excellent prognosis, while diffusely infiltrative tumors, although slow-growing, are eventually fatal (Sturm et al. in J Clin Oncol 35:2370-2377, 2017). This chapter reviews the shared and unique individual features of the benign glioma including diffuse glioma, pilocytic astrocytoma and pilomyxoid astrocytoma (PMA), subependymal giant cell astrocytoma (SEGA), pleomorphic xanthoastrocytoma (PXA), subependymoma (SE), angiocentric glioma (AG), and chordoid glioma (CG). Also discussed is ganglioglioma (GG), a mixed neuronal-glial tumor that represents a notable diagnosis in the differential for other LGG (Wesseling and Capper 2018). Ependymomas of the brain and spinal cord, including major histologic subtypes, are discussed in other chapters.

Feasibility of glioblastoma tissue response mapping with physiologic BOLD imaging using precise oxygen and carbon dioxide challenge

OBJECTIVES

Innovative physiologic MRI development focuses on depiction of heterogenous vascular and metabolic features in glioblastoma. For this feasibility study, we employed blood oxygenation level-dependent (BOLD) MRI with standardized and precise carbon dioxide (CO₂) and oxygen (O₂) modulation to investigate specific tumor tissue response patterns in patients with newly diagnosed glioblastoma.

MATERIALS AND METHODS

Seven newly diagnosed untreated patients with suspected glioblastoma were prospectively included to undergo a BOLD study with combined CO₂ and O₂ standardized protocol. %BOLD signal change/mmHg during hypercapnic, hypoxic, and hyperoxic stimulus was calculated in the whole brain, tumor lesion and segmented volumes of interest (VOI) [contrast-enhancing (CE) - tumor, necrosis and edema] to analyze their tissue response patterns.

RESULTS

Quantification of BOLD signal change after gas challenges can be used to identify specific responses to standardized stimuli in glioblastoma patients. Integration of this approach with automatic VOI segmentation grants improved characterization of tumor subzones and edema. Magnitude of BOLD signal change during the 3 stimuli can be visualized at voxel precision through color-coded maps overlayed onto whole brain and identified VOIs.

CONCLUSIONS

Our preliminary investigation shows good feasibility of BOLD with standardized and precise CO₂ and O₂ modulation as an emerging physiologic imaging technique to detail specific glioblastoma characteristics. The unique tissue response patterns generated can be further investigated to better detail glioblastoma lesions and gauge treatment response.

BOLD Coupling between Lesioned and Healthy Brain Is Associated with Glioma Patients' Recovery

Predicting functional outcomes after surgery and early adjuvant treatment is difficult due to the complex, extended, interlocking brain networks that underpin cognition. The aim of this study was to test glioma functional interactions with the rest of the brain, thereby identifying the risk factors of cognitive recovery or deterioration. Seventeen patients with diffuse non-enhancing glioma (aged 22-56 years) were longitudinally MRI scanned and cognitively assessed before and after surgery and during a 12-month recovery period (55 MRI scans in total after exclusions). We initially found, and then replicated in an independent dataset, that the spatial correlation pattern between regional and global BOLD signals (also known as global signal topography) was associated with tumour occurrence. We then estimated the coupling between the BOLD signal from within the tumour and the signal extracted from different brain tissues. We observed that the normative global signal topography is reorganised in glioma patients during the recovery period. Moreover, we found that the BOLD signal within the tumour and lesioned brain was coupled with the global signal and that this coupling was associated with cognitive recovery. Nevertheless, patients did not show any apparent disruption of functional connectivity within canonical functional networks. Understanding how tumour infiltration and coupling are related to patients' recovery represents a major step forward in prognostic development.

BOLD Asynchrony Elucidates Tumor Burden in IDH-Mutated Gliomas

BACKGROUND

Gliomas comprise the most common type of primary brain tumor, are highly invasive, and often fatal. IDH-mutated gliomas are particularly challenging to image and there is currently no clinically accepted method for identifying the extent of tumor burden in these neoplasms. This uncertainty poses a challenge to clinicians who must balance the need to treat the tumor while sparing healthy brain from iatrogenic damage. The purpose of this study was to investigate the feasibility of using resting-state blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) to detect glioma-related asynchrony in vascular dynamics for distinguishing tumor from healthy brain.

METHODS

Twenty-four stereotactically localized biopsies were obtained during open surgical resection from ten treatment-naïve patients with IDH-mutated gliomas who received standard of care preoperative imaging as well as echo-planar resting-state BOLD fMRI. Signal intensity for BOLD asynchrony and standard of care imaging was compared to cell counts of total cellularity (H&E), tumor density (IDH1 & Sox2), cellular proliferation (Ki67), and neuronal density (NeuN), for each corresponding sample.

RESULTS

BOLD asynchrony was directly related to total cellularity (H&E, p = 4 x 10 -5), tumor density (IDH1, p = 4 x 10 -5; Sox2, p = 3 x 10 -5), cellular proliferation (Ki67, p = 0.002), and as well as inversely related to neuronal density (NeuN, p = 1 x 10 -4).

CONCLUSIONS

Asynchrony in vascular dynamics, as measured by resting-state BOLD fMRI, correlates with tumor burden and provides a radiographic delineation of tumor boundaries in IDH-mutated gliomas.

Asynchrony in Peritumoral Resting-State Blood Oxygen Level-Dependent fMRI Predicts Meningioma Grade and Invasion

BACKGROUND AND PURPOSE

Meningioma grade is determined by histologic analysis, with detectable brain invasion resulting in a diagnosis of grade II or III tumor. However, tissue undersampling is a common problem, and invasive parts of the tumor can be missed, resulting in the incorrect assignment of a lower grade. Radiographic biomarkers may be able to improve the diagnosis of grade and identify targets for biopsy. Prior work in patients with gliomas has shown that the resting-state blood oxygen level-dependent fMRI signal within these tumors is not synchronous with normal brain. We hypothesized that blood oxygen level-dependent asynchrony, a functional marker of vascular dysregulation, could predict meningioma grade.

MATERIALS AND METHODS

We identified 25 patients with grade I and 11 patients with grade II or III meningiomas. Blood oxygen level-dependent time-series were extracted from the tumor and the radiographically normal control hemisphere and were included as predictors in a multiple linear regression to generate a blood oxygen level-dependent asynchrony map, in which negative values signify synchronous and positive values signify asynchronous activity relative to healthy brain. Masks of blood oxygen level-dependent asynchrony were created for each patient, and the fraction of the mask that extended beyond the contrast-enhancing tumor was computed.

RESULTS

The spatial extent of blood oxygen level-dependent asynchrony was greater in high (grades II and III) than in low (I) grade tumors (P < 0.001) and could discriminate grade with high accuracy (area under the curve = 0.88).

CONCLUSIONS

Blood oxygen level-dependent asynchrony radiographically discriminates meningioma grade and may provide targets for biopsy collection to aid in histologic diagnosis.

Hemisphere-Specific Functional Remodeling and Its Relevance to Tumor Malignancy of Cerebral Glioma Based on Resting-State Functional Network Analysis

BACKGROUND

Functional remodeling may vary with tumor aggressiveness of glioma. Investigation of the functional remodeling is expected to provide scientific relevance of tumor characterization and disease management of glioma. In this study, we aimed to investigate the functional remodeling of the contralesional hemisphere and its utility in predicting the malignant grade of glioma at the individual level with multivariate logistic regression (MLR) analysis.

SUBJECTS AND METHODS

One hundred and twenty-six right-handed subjects with histologically confirmed cerebral glioma were included with 80 tumors located in the left hemisphere (LH) and 46 tumors located in the right hemisphere (RH). Resting-state functional networks of the contralesional hemisphere were constructed using the human brainnetome atlas based on resting-state fMRI data. Functional connectivity and topological features of functional networks were quantified. The performance of functional features in predicting the glioma grade was evaluated using area under (AUC) the receiver operating characteristic curve (ROC). The dataset was divided into training and validation datasets. Features with high AUC values in malignancy classification in the training dataset were determined as predictive features. An MLR model was constructed based on predictive features and its classification performance was evaluated on the training and validation datasets with 10-fold cross validation.

RESULTS

Predictive functional features showed apparent hemispheric specifications. MLR classification models constructed with age and predictive functional connectivity features (AUC of 0.853 ± 0.079 and 1.000 ± 0.000 for LH and RH group, respectively) and topological features (AUC of 0.788 ± 0.150 and 0.897 ± 0.165 for LH and RH group, respectively) achieved efficient performance in predicting the malignant grade of gliomas.

CONCLUSION

Functional remodeling of the contralesional hemisphere was hemisphere-specific and highly predictive of the malignant grade of glioma. Network approach provides a novel pathway that may innovate glioma characterization and management at the individual level.

Second-Generation Digital Health Platforms: Placing the Patient at the Center and Focusing on Clinical Outcomes

Artificial intelligence (AI) digital health systems have drawn much attention over the last decade. However, their implementation into medical practice occurs at a much slower pace than expected. This paper reviews some of the achievements of first-generation AI systems, and the barriers facing their implementation into medical practice. The development of second-generation AI systems is discussed with a focus on overcoming some of these obstacles. Second-generation systems are aimed at focusing on a single subject and on improving patients' clinical outcomes. A personalized closed-loop system designed to improve end-organ function and the patient's response to chronic therapies is presented. The system introduces a platform which implements a personalized therapeutic regimen and introduces quantifiable individualized-variability patterns into its algorithm. The platform is designed to achieve a clinically meaningful endpoint by ensuring that chronic therapies will have sustainable effect while overcoming compensatory mechanisms associated with disease progression and drug resistance. Second-generation systems are expected to assist patients and providers in adopting and implementing of these systems into everyday care.

Emerging Techniques in Imaging of Glioma Microenvironment

Magnetic resonance imaging (MRI) has been the cornerstone of imaging of brain tumors in the past 4 decades. Conventional MRI remains the workhorse for neuro-oncologic imaging, not only for basic information such as location, extent, and navigation but also able to provide information regarding proliferation and infiltration, angiogenesis, hemorrhage, and more. More sophisticated MRI sequences have extended the ability to assess and quantify these features; for example, permeability and perfusion acquisitions can assess blood-brain barrier disruption and angiogenesis, diffusion techniques can assess cellularity and infiltration, and spectroscopy can address metabolism. Techniques such as fMRI and diffusion fiber tracking can be helpful in diagnostic planning for resection and radiation therapy, and more sophisticated iterations of these techniques can extend our understanding of neurocognitive effects of these tumors and associated treatment responses and effects. More recently, MRI has been used to go beyond such morphological, physiological, and functional characteristics to assess the tumor microenvironment. The current review highlights multiple recent and emerging approaches in MRI to characterize the tumor microenvironment.

The Utility of Liquid Biopsies in Radiation Oncology

The use of therapeutic radiation is primarily guided by clinicopathologic factors and medical imaging, whereas molecular biomarkers currently play a comparatively minor role in most settings. Liquid biopsies provide a rich source of noninvasive tumor-specific biomarkers and are amenable to repeated and noninvasive assessment. Here, we review the current status of liquid biopsies and their potential impact on the field of radiation oncology. We focus on established and emerging approaches to analyze circulating tumor DNA and circulating tumor cells from peripheral blood. These promising classes of biomarkers could have an outsized impact on cancer management by meaningfully stratifying patients into risk groups, tracking radiation therapy efficacy during and after treatment, and identifying patients with radiosensitive or radioresistant disease. Finally, we highlight opportunities for future investigation including the need for prospective interventional studies employing liquid biopsies to guide the management of radiation therapy-treated patients.

Glioma-Induced Alterations in Neuronal Activity and Neurovascular Coupling during Disease Progression

Diffusely infiltrating gliomas are known to cause alterations in cortical function, vascular disruption, and seizures. These neurological complications present major clinical challenges, yet their underlying mechanisms and causal relationships to disease progression are poorly characterized. Here, we follow glioma progression in awake Thy1-GCaMP6f mice using in vivo wide-field optical mapping to monitor alterations in both neuronal activity and functional hemodynamics. The bilateral synchrony of spontaneous neuronal activity gradually decreases in glioma-infiltrated cortical regions, while neurovascular coupling becomes progressively disrupted compared to uninvolved cortex. Over time, mice develop diverse patterns of high amplitude discharges and eventually generalized seizures that appear to originate at the tumors' infiltrative margins. Interictal and seizure events exhibit positive neurovascular coupling in uninfiltrated cortex; however, glioma-infiltrated regions exhibit disrupted hemodynamic responses driving seizure-evoked hypoxia. These results reveal a landscape of complex physiological interactions occurring during glioma progression and present new opportunities for exploring novel biomarkers and therapeutic targets.

Single-cell transcriptome analysis of lineage diversity in high-grade glioma

BACKGROUND

Despite extensive molecular characterization, we lack a comprehensive understanding of lineage identity, differentiation, and proliferation in high-grade gliomas (HGGs).

METHODS

We sampled the cellular milieu of HGGs by profiling dissociated human surgical specimens with a high-density microwell system for massively parallel single-cell RNA-Seq. We analyzed the resulting profiles to identify subpopulations of both HGG and microenvironmental cells and applied graph-based methods to infer structural features of the malignantly transformed populations.

RESULTS

While HGG cells can resemble glia or even immature neurons and form branched lineage structures, mesenchymal transformation results in unstructured populations. Glioma cells in a subset of mesenchymal tumors lose their neural lineage identity, express inflammatory genes, and co-exist with marked myeloid infiltration, reminiscent of molecular interactions between glioma and immune cells established in animal models. Additionally, we discovered a tight coupling between lineage resemblance and proliferation among malignantly transformed cells. Glioma cells that resemble oligodendrocyte progenitors, which proliferate in the brain, are often found in the cell cycle. Conversely, glioma cells that resemble astrocytes, neuroblasts, and oligodendrocytes, which are non-proliferative in the brain, are generally non-cycling in tumors.

CONCLUSIONS

These studies reveal a relationship between cellular identity and proliferation in HGG and distinct population structures that reflects the extent of neural and non-neural lineage resemblance among malignantly transformed cells.